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Title: A divide-and-conquer strategy using feature relevance and expert knowledge for enhancing a data mining approach to bank telemarketing
Authors: Moro, S.
Cortez, P.
Rita, P.
Keywords: Banking
Data mining
Divide and conquer
Feature selection
Issue Date: 2018
Publisher: John Wiley and Sons
Abstract: The discovery of knowledge through data mining provides a valuable asset for addressing decision making problems. Although a list of features may characterize a problem, it is often the case that a subset of those features may influence more a certain group of events constituting a sub-problem within the original problem. We propose a divide-and-conquer strategy for data mining using both the data-based sensitivity analysis for extracting feature relevance and expert evaluation for splitting the problem of characterizing telemarketing contacts to sell bank deposits. As a result, the call direction (inbound/outbound) was considered the most suitable candidate feature. The inbound telemarketing sub-problem re-evaluation led to a large increase in targeting performance, confirming the benefits of such approach and considering the importance of telemarketing for business, in particular in bank marketing.
Peer reviewed: yes
DOI: 10.1111/exsy.12253
ISSN: 0266-4720
Accession number: WOS:000434639000004
Appears in Collections:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica
CIS-RI - Artigos em revistas científicas internacionais com arbitragem científica

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